Skip to content

Latest commit

 

History

History
223 lines (174 loc) · 20.6 KB

sec-design-deep-analysis.md

File metadata and controls

223 lines (174 loc) · 20.6 KB

Deep Security Analysis of jackson-databind

1. Objective, Scope, and Methodology

Objective:

The objective of this deep security analysis is to conduct a thorough examination of the jackson-databind library's key components, identify potential security vulnerabilities, assess their impact, and provide actionable mitigation strategies. The analysis will focus on:

  • Polymorphic Deserialization: Analyzing the security implications of Jackson's handling of polymorphic types, a historically significant source of vulnerabilities.
  • Input Validation: Evaluating the library's input validation mechanisms and their effectiveness against various injection attacks.
  • Dependency Management: Assessing the security risks associated with the library's dependencies.
  • Configuration Security: Identifying potentially dangerous configurations and recommending secure defaults.
  • Data Handling: Analyzing how the library handles data and potential risks related to data exposure or corruption.
  • Integration with Security Tooling: Providing recommendations for integrating the library with security tools.

Scope:

This analysis focuses on the jackson-databind library itself, version 2.x (as it is the most widely used). It considers the library's code, documentation, and known vulnerabilities. It does not cover:

  • Specific applications using jackson-databind. Application-level security is the responsibility of the application developers.
  • Other Jackson modules (e.g., data format modules like jackson-dataformat-xml) except where they directly interact with jackson-databind's core functionality.
  • The underlying operating system, JVM, or hardware.

Methodology:

  1. Code Review: Examine the source code of jackson-databind (available on GitHub) to understand its internal workings and identify potential vulnerabilities. This includes focusing on areas identified in the Objective.
  2. Documentation Review: Analyze the official Jackson documentation, including Javadocs, security advisories, and best practices guides.
  3. Vulnerability Research: Review known vulnerabilities (CVEs) associated with jackson-databind and analyze their root causes and fixes.
  4. Architecture Inference: Based on the codebase and documentation, infer the library's architecture, components, and data flow, as presented in the provided C4 diagrams.
  5. Threat Modeling: Identify potential threats based on the library's functionality and deployment scenarios.
  6. Mitigation Strategy Development: Propose specific, actionable mitigation strategies for identified threats, tailored to jackson-databind.
  7. Tooling Integration: Recommend security tools and practices for use during development and deployment.

2. Security Implications of Key Components

Based on the C4 diagrams and the provided design review, the following key components are analyzed:

  • ObjectMapper (Main API):

    • Security Implications: This is the primary entry point, and its configuration significantly impacts security. Misconfiguration (e.g., enabling default typing) can lead to RCE vulnerabilities. It acts as a facade, delegating to other components, so its security posture is tied to the security of those components.
    • Threats: RCE via insecure configuration, denial of service via excessive resource consumption.
    • Mitigation:
      • Never enable default typing globally (ObjectMapper.enableDefaultTyping()). This is the most critical mitigation.
      • Use a restrictive TypeResolverBuilder or a custom TypeResolverBuilder with a whitelist of allowed classes for polymorphic deserialization.
      • Regularly review and update the ObjectMapper configuration to ensure it remains secure.
      • Sanitize input before passing it to ObjectMapper. While ObjectMapper does some input validation, relying solely on it is insufficient. The application is responsible for primary input validation.

  • ObjectReader (Deserialization) & ObjectWriter (Serialization):

    • Security Implications: ObjectReader is where the most critical deserialization vulnerabilities reside. ObjectWriter is generally less risky, but insecure handling of sensitive data during serialization could lead to information disclosure.
    • Threats: RCE (primarily ObjectReader), information disclosure (primarily ObjectWriter), denial of service.
    • Mitigation:
      • ObjectReader: Follow all mitigations for ObjectMapper related to polymorphic deserialization. Use readValue() methods that take a TypeReference or Class argument to explicitly specify the expected type, avoiding reliance on type information embedded in the JSON. Avoid using deprecated methods that are known to be less secure.
      • ObjectWriter: Use annotations like @JsonIgnore and @JsonView to control which fields are serialized, preventing accidental exposure of sensitive data. Consider using custom serializers (JsonSerializer) for sensitive data to implement encryption or redaction.

  • DeserializationContext & SerializationContext (State Management):

    • Security Implications: These contexts hold configuration and state during the (de)serialization process. Vulnerabilities here could potentially allow attackers to influence the process or access internal data.
    • Threats: Configuration manipulation, information disclosure, denial of service.
    • Mitigation:
      • Avoid directly modifying the context objects unless absolutely necessary. Rely on the provided configuration methods of ObjectMapper, ObjectReader, and ObjectWriter.
      • Ensure that custom implementations of DeserializationProblemHandler or other context-related classes do not introduce vulnerabilities.

  • DeserializerCache & SerializerCache (Caching):

    • Security Implications: While primarily for performance, caching could theoretically be a target for attacks if the cache is not properly managed or if it stores sensitive data insecurely.
    • Threats: Denial of service (cache poisoning), information disclosure (if sensitive data is cached inappropriately).
    • Mitigation:
      • The default caching mechanisms in jackson-databind are generally safe. However, if you implement custom caching, ensure that it is thread-safe and does not expose sensitive data.
      • Limit the size of the cache to prevent excessive memory consumption.

  • BeanDeserializer & BeanSerializer (POJO Handling):

    • Security Implications: These components handle the core logic for (de)serializing Java beans. Vulnerabilities here could impact a wide range of applications. Polymorphic deserialization vulnerabilities often manifest within BeanDeserializer.
    • Threats: RCE (primarily BeanDeserializer), information disclosure (primarily BeanSerializer).
    • Mitigation:
      • BeanDeserializer: This is a critical area for polymorphic deserialization vulnerabilities. Strictly control which classes can be instantiated during deserialization using whitelists and custom TypeResolverBuilder implementations. Avoid using @JsonTypeInfo with Id.CLASS or Id.MINIMAL_CLASS unless absolutely necessary and with a very restrictive whitelist. Prefer Id.NAME with a well-defined set of subtypes.
      • BeanSerializer: Use annotations like @JsonIgnore and @JsonView to control which fields are serialized.

  • JsonDeserializer & JsonSerializer (Specific Types):

    • Security Implications: Custom (de)serializers allow developers to implement their own logic, which can introduce vulnerabilities if not done carefully.
    • Threats: RCE, information disclosure, denial of service, any vulnerability that can be introduced by custom code.
    • Mitigation:
      • Thoroughly review and test any custom (de)serializers. Pay close attention to input validation, error handling, and secure coding practices.
      • Avoid using untrusted input to construct class names or perform other security-sensitive operations within custom (de)serializers.
      • Prefer using built-in (de)serializers whenever possible.

  • Jackson Core API:

    • Security Implications: This layer handles low-level parsing. Vulnerabilities here could affect all higher-level components.
    • Threats: Buffer overflows, denial of service via crafted input.
    • Mitigation:
      • Rely on the Jackson team to maintain the security of the core API. Keep Jackson Core updated.
      • Limit input size to prevent excessively large JSON documents from causing denial-of-service.

3. Architecture, Components, and Data Flow (Inferred)

The provided C4 diagrams and design review provide a good overview of the architecture. The key data flow is:

  1. Serialization:

    • Application calls ObjectMapper.writeValue() (or similar methods).
    • ObjectMapper creates an ObjectWriter and SerializationContext.
    • ObjectWriter uses BeanSerializer (or other serializers) to convert the Java object to JSON tokens.
    • SerializationContext manages the state and configuration.
    • SerializerCache is used to cache serializer instances.
    • The JSON tokens are written to the output (e.g., a stream, a string).

  2. Deserialization:

    • Application calls ObjectMapper.readValue() (or similar methods).
    • ObjectMapper creates an ObjectReader and DeserializationContext.
    • ObjectReader uses BeanDeserializer (or other deserializers) to parse the JSON tokens and create Java objects.
    • DeserializationContext manages the state and configuration.
    • DeserializerCache is used to cache deserializer instances.
    • The resulting Java object is returned to the application.

Polymorphic Deserialization Flow:

  1. ObjectReader encounters a field with polymorphic type information (e.g., @JsonTypeInfo annotation).
  2. ObjectReader uses a TypeResolverBuilder to determine the concrete class to instantiate based on the type information in the JSON.
  3. DeserializationContext resolves the type ID to a JavaType.
  4. BeanDeserializer (or a specialized deserializer) creates an instance of the resolved class and populates its fields.
  5. If the resolved class is not allowed (based on configuration or whitelists), an exception should be thrown. This is where the security checks are crucial.

4. Specific Security Considerations and Recommendations

Given the nature of jackson-databind as a data-binding library, the following specific security considerations are paramount:

  • Untrusted Input: The most critical consideration is that jackson-databind should never be used to deserialize untrusted input without strict security controls. Untrusted input refers to any data that originates from outside the application's trust boundary (e.g., user input, data from external APIs, data from databases that could be manipulated by attackers).
  • Polymorphic Deserialization: This is the primary attack vector for RCE vulnerabilities in jackson-databind. The library's default behavior (prior to version 2.10) was to allow deserialization of arbitrary classes based on type information embedded in the JSON, which could be exploited by attackers.
  • Denial of Service: Attackers can craft malicious JSON input to cause excessive resource consumption (CPU, memory), leading to denial of service. This can be achieved through deeply nested objects, large arrays, or other techniques.
  • Data Exposure: Careless configuration or use of custom serializers can lead to the exposure of sensitive data in the serialized JSON output.

Specific Recommendations:

  1. Disable Default Typing: As mentioned earlier, never use ObjectMapper.enableDefaultTyping(). This is the single most important security measure.

  2. Use Safe Type Handling:

    • Whitelist Approach (Strongly Recommended): Configure a custom TypeResolverBuilder that explicitly whitelists the classes allowed for polymorphic deserialization. This is the most secure approach. 
      // Example using a custom TypeResolverBuilder with a whitelist
SimpleTypeResolverBuilder typeResolverBuilder = new SimpleTypeResolverBuilder(ObjectMapper.DefaultTyping.NON_FINAL);
typeResolverBuilder = typeResolverBuilder.init(JsonTypeInfo.Id.NAME, null);
typeResolverBuilder = typeResolverBuilder.inclusion(JsonTypeInfo.As.PROPERTY);
typeResolverBuilder = typeResolverBuilder.typeProperty("@type");
typeResolverBuilder = typeResolverBuilder.typeIdValidator(new ClassNameWhitelistValidator("com.example.MyClass1", "com.example.MyClass2")); // Whitelist

ObjectMapper mapper = JsonMapper.builder()
        .typeResolver(typeResolverBuilder)
        .build();
    • @JsonTypeInfo with Id.NAME (Recommended with Caution): Use @JsonTypeInfo with Id.NAME and a well-defined set of subtypes using @JsonSubTypes. This is more secure than Id.CLASS or Id.MINIMAL_CLASS, but still requires careful management of the allowed subtypes. 
      @JsonTypeInfo(use = JsonTypeInfo.Id.NAME, include = JsonTypeInfo.As.PROPERTY, property = "type")
@JsonSubTypes({
    @JsonSubTypes.Type(value = Dog.class, name = "dog"),
    @JsonSubTypes.Type(value = Cat.class, name = "cat")
})
abstract class Animal { }

@JsonTypeName("dog")
class Dog extends Animal { }

@JsonTypeName("cat")
class Cat extends Animal { }
    • Avoid Id.CLASS and Id.MINIMAL_CLASS: These options are highly vulnerable and should be avoided unless absolutely necessary and with a very strict whitelist.
    • Use activateDefaultTyping() with a PolymorphicTypeValidator (for Jackson 2.10+): Jackson 2.10 introduced PolymorphicTypeValidator (PTV) to provide a safer way to enable default typing. Use activateDefaultTyping() with a custom PTV that implements your whitelisting logic. This is preferred over the older enableDefaultTyping() methods. 
      // Example using PolymorphicTypeValidator (Jackson 2.10+)
PolymorphicTypeValidator ptv = ...; // Implement your custom validator
ObjectMapper mapper = JsonMapper.builder()
        .activateDefaultTyping(ptv, ObjectMapper.DefaultTyping.NON_FINAL)
        .build();

  3. Input Validation (Application Responsibility): While jackson-databind performs some input validation, the application using the library is primarily responsible for validating input before passing it to Jackson. This includes:

    • Schema Validation: If possible, use a JSON Schema validator to validate the structure and data types of the JSON input.
    • Length Limits: Enforce limits on the length of strings and the size of arrays and objects to prevent denial-of-service attacks.
    • Data Sanitization: Sanitize input to remove or escape potentially dangerous characters.
    • Content Type Validation: Verify that the Content-Type header is application/json (or another expected JSON-compatible type).

  4. Dependency Management:

    • Keep Jackson Updated: Regularly update jackson-databind and its dependencies (especially jackson-core and jackson-annotations) to the latest versions to receive security patches.
    • Use a Dependency Management Tool: Use a tool like Maven or Gradle to manage dependencies and automatically check for updates.
    • Software Composition Analysis (SCA): Use SCA tools (e.g., OWASP Dependency-Check, Snyk) to identify and manage vulnerabilities in third-party dependencies, including Jackson.

  5. Secure Configuration:

    • Disable Unnecessary Features: Disable any Jackson features that are not needed by your application. This reduces the attack surface.
    • Configure Deserialization Features: Use DeserializationFeature to control various aspects of deserialization. For example, disable FAIL_ON_UNKNOWN_PROPERTIES if you are sure that unknown properties are not a security risk.
    • Configure Serialization Features: Use SerializationFeature to control serialization. For example, enable WRITE_DATES_AS_TIMESTAMPS to avoid potential timezone-related issues.

  6. Data Handling:

    • Avoid Serializing Sensitive Data: If possible, avoid serializing sensitive data (e.g., passwords, API keys) in the first place.
    • Use Annotations: Use @JsonIgnore, @JsonView, and other annotations to control which fields are serialized and deserialized.
    • Custom Serializers/Deserializers: For sensitive data, consider using custom serializers and deserializers to implement encryption, redaction, or other security measures.
    • Data Minimization: Only serialize the data that is absolutely necessary.

  7. Error Handling:

    • Avoid Exposing Internal Details: Do not expose internal error messages or stack traces to users. Log detailed error information securely and provide generic error messages to users.
    • Handle Exceptions Gracefully: Handle all exceptions thrown by jackson-databind gracefully to prevent application crashes or unexpected behavior.

  8. Testing:

    • Fuzz Testing: Use fuzz testing tools to provide invalid or unexpected JSON input to jackson-databind and identify potential vulnerabilities.
    • Unit and Integration Tests: Write comprehensive unit and integration tests to cover all code paths, including error handling and edge cases.
    • Regression Tests: Include regression tests for known vulnerabilities to ensure that they are not reintroduced in future versions.

  9. Monitoring and Logging:

    • Log Deserialization Events: Log information about deserialization events, including the classes being deserialized and any errors that occur. This can help detect and investigate potential attacks.
    • Monitor Resource Consumption: Monitor the CPU and memory usage of your application to detect potential denial-of-service attacks.

  10. Integration with Security Tooling:

    • Static Application Security Testing (SAST): Integrate SAST tools (e.g., FindBugs, SpotBugs, SonarQube) into your build process to identify potential vulnerabilities in your code and in jackson-databind.
    • Dynamic Application Security Testing (DAST): Use DAST tools (e.g., OWASP ZAP, Burp Suite) to test your application at runtime and identify vulnerabilities related to JSON processing.
    • Software Composition Analysis (SCA): As mentioned earlier, use SCA tools to identify and manage vulnerabilities in jackson-databind and its dependencies.

5. Addressing Questions and Assumptions

  • Compliance Requirements: Applications using jackson-databind may need to comply with various regulations (GDPR, HIPAA, PCI DSS) depending on the data they handle. This requires careful consideration of data storage, processing, and transmission. jackson-databind itself does not directly address these requirements; the application using it must implement appropriate controls.
  • Threat Model: The threat model depends on the application. For web applications, common threats include RCE, XSS (if JSON is used in HTML output without proper escaping), and denial of service. For internal services, the threat model may be different, but RCE and denial of service are still relevant.
  • Security Expertise: Developers using jackson-databind should have a good understanding of security principles, especially related to input validation, polymorphic deserialization, and secure configuration. The documentation should provide clear guidance, but developers are ultimately responsible for using the library securely.
  • Performance Requirements: Performance is a key consideration for jackson-databind. The library is designed to be high-performance, but certain configurations or usage patterns can impact performance. Profiling and performance testing are recommended.
  • Known Limitations: The main known limitation is the historical vulnerability to polymorphic deserialization attacks. This has been addressed in recent versions with the introduction of PolymorphicTypeValidator, but developers must still configure the library securely.

The assumptions made in the design review are generally reasonable. The most important assumption is that applications using the library will handle sensitive data appropriately. This is crucial because jackson-databind is a data-binding library, and the security of the data it processes depends on the application's security practices.